Stored program controlled systems generally are limited in performance capacity by their data processing resources, and more specifically, by the processing capacity of its central processing unit. If various system tasks each take a certain number of central processor cycles, and the total number of such cycles available in any unit of time is limited, then the number of system tasks which can be performed in any given time period is also limited. For example, in terms of a stored program controlled telephone switching system, this limitation means that the number of telephone call connections which can be set up and released by the system during any given interval is limited.
In a real-time system, task execution demands and the central processor resources required to respond to these demands tend to vary significantly with time and in a partly random fashion. Thus, predictions of system capacity based on simulation of inputs to the system tend to be imperfect because they lack a realistic random element. It is particularly important to have accurate estimates of residual capacity of working system installations since additions of equipment to these systems and long term growth plans must be made on the basis of these estimates. For example, capacity information for an existing telephone central office is important to telephone engineers in the planning of growth additions to that central office.
In the past, estimates of capacity have typically been made through a study of the available central processor resources during periods of light and heavy processing loads, and an extrapolation of these available resources as a function of the number of system tasks carried out during these periods. Artifical load, applied through the use of load boxes for generating large numbers of inputs to augment a real load in the system, also has been used to help estimate capacity. These estimates are not always sufficiently accurate. For example, in a telephone switching system, these estimates tend to be limited in their accuracy by the special characteristics of a particular installation, including variations in the percentages of different types of traffic (incoming, outgoing, interoffice, etc.) and variations in the special habits of the customers connected to a particular installation (retrial rate, busy rate, etc.).
It is an object of this invention to provide a method and apparatus for making realistic estimates of capacity of an existing system by simulating incremental load increases while the system is carrying live load. It is a further object of this invention to drive a system into an overload state by depriving the system of central processor resources in a uniform manner, affecting all system tasks equally. It is a still further object of this invention to allow system performance to be measured in a live system that is thus driven into an overload state.
Still another object of this invention is to allow the realistic loading of a system that is carrying moderate mounts of live load to an overload state and providing indications of the performance of the system in such an overload state, and more particularly, to allow evaluation of system overload response strategies in an overload state.